SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization Class Reference

Inheritance diagram for SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization:

## Public Member Functions | |

def | __defaults__ (self) |

def | build_surrogate (self) |

def | iterative_optimization (self) |

Public Member Functions inherited from SUAVE.Core.Data.Data | |

def | __getattribute__ (self, k) |

def | __setattr__ (self, k, v) |

def | __delattr__ (self, k) |

def | __new__ (cls, *args, **kwarg) |

def | typestring (self) |

def | dataname (self) |

def | __str__ (self, indent='') |

def | __init__ (self, *args, **kwarg) |

def | __iter__ (self) |

def | itervalues (self) |

def | values (self) |

def | update (self, other) |

def | append_or_update (self, other) |

def | get_bases (self) |

def | append (self, value, key=None) |

def | deep_set (self, keys, val) |

def | deep_get (self, keys) |

def | pack_array (self, output='vector') |

def | unpack_array (self, M) |

def | do_recursive (self, method, other=None, default=None) |

## Public Attributes | |

sample_plan | |

problem | |

optimizer | |

surrogate_model | |

optimization_filename | |

number_of_points | |

max_iterations | |

Takes a SUAVE Optimization problem, builds a surrogate around it, and iteratively finds the optimum of the surrogate, then samples at that point. Stops when you hit max_iterations or it converges Assumptions: You're okay with represeting your problem with a surrogate Source: N/A

def SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization.__defaults__ | ( | self | ) |

This sets the default values. Assumptions: None Source: N/A Inputs: None Outputs: None Properties Used: None

Reimplemented from SUAVE.Core.Data.Data.

def SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization.build_surrogate | ( | self | ) |

Builds a surrogate for the problem Assumptions: None Source: N/A Inputs: None Outputs: None Properties Used: None

def SUAVE.Optimization.Surrogate_Optimization.Surrogate_Optimization.iterative_optimization | ( | self | ) |

Optimizes iteratively Assumptions: None Source: N/A Inputs: None Outputs: output_real [float] surrogate_problem [surrogate] Properties Used: None

The documentation for this class was generated from the following file:

- /Users/emiliobotero/Dropbox/SUAVE/SUAVE/trunk/SUAVE/Optimization/Surrogate_Optimization.py